BMC Medicine最新文献

Background: Spontaneous preterm birth (sPTB) remains a major contributor to neonatal morbidity and mortality, with limited reliable early prediction tools. Existing biomarkers, such as the insulin-like growth factor-binding protein 4 (IBP4) to sex hormone-binding globulin (SHBG) ratio, offer modest predictive performance and are restricted to mid-gestation use (18-20 weeks), limiting their utility for timely intervention. We aimed to develop and validate a novel serological test based on early-gestational sampling to predict the risk of sPTB.

Methods: We conducted a meta-analysis of 18 placental transcriptomic datasets to identify candidate genes associated with sPTB, resulting in 21 protein candidates tested by targeted proteomics. We developed a three-protein panel (glutathione peroxidase 3, GPX3; nidogen-1, NID1; and pappalysin-2, PAPPA2) and validated it in four independent cohorts (456 subjects and 1048 serum specimens) from the USA and Asia. Longitudinal serum samples were collected from 5 weeks and were analyzed using mass spectrometry and ELISA platforms. Predictor performance was compared to the IBP4/SHBG ratio.

Results: The three-protein predictor (GPX3, NID1, and PAPPA2) demonstrated reproducible and superior performance across cohorts: AUC 0.74 (95% CI 0.59-0.88) in Alabama, 0.93 (95% CI 0.88-0.99) in California, 0.80 (95% CI 0.75-0.85) in Asia 1, and 0.83 (95% CI 0.70-0.95) in Asia 2. This outperformed the IBP4/SHBG ratio, which achieved AUCs of 0.68 (95% CI 0.50-0.89), 0.77 (95% CI 0.67-0.88), 0.59 (95% CI 0.52-0.65), and 0.61 (95% CI 0.50-0.75), respectively. Across obstetric trimesters, the three-protein panel maintained high predictive accuracy in the first and second trimesters (AUROC 0.82-0.97), the window when preventive interventions such as progesterone, cerclage, and low-dose aspirin are most effective. Kaplan-Meier analyses confirmed significantly earlier delivery among high-risk pregnancies identified by the three-protein panel.

Conclusions: This maternal serum test provides a reliable approach for early risk assessment of sPTB. The three-protein panel demonstrated reproducible performance across cohorts and across PPROM-positive and PPROM-negative phenotypes, with the strongest discrimination in the first and second trimesters, when preventive therapies such as progesterone or cerclage are most effective. These findings support its potential as an early, clinically actionable screening tool for improving pregnancy outcomes.

Background: Household cannabis use is a risk factor for adolescents' mental health problems. However, little is known about the association of the cessation and psychological impairments in affected adolescents. This study examined the associations of household cannabis cessation and adolescents' mental health outcomes and potential pathways.

Methods: This cohort study used data from the Adolescent Brain Cognitive Development study and included adolescents aged 10-13 years with household cannabis use within 12 months at wave 2. Household cannabis cessation was defined as the absence of cannabis use by household members (excluding the adolescent participant) at wave 3 among households that reported use at wave 2. Internalizing and externalizing problems were assessed using the Child Behavior Checklist, and psychotic-like experiences (PLEs) were evaluated using the Prodromal Questionnaire-Brief Child Version. Family conflict and sleep problems were assessed using the Family Environment subscale and the Sleep Disturbance Scale for Children, respectively. Demographic and psychometric confounders were balanced with propensity score matching (PSM). Linear regression was applied to investigate the associations between cessation and mental health outcomes. Mediation analyses of family conflict and adolescent sleep problems were performed. We further considered the influence of genetic predisposition to cannabis use disorder (CUD) and examined whether brain connectivity patterns, measured by resting-state fMRI, modified the relationships.

Results: Of the 1426 adolescents exposed to household cannabis within 12 months, 438 (30.7%) were no longer exposed by wave 3. After PSM, cessation was associated with lower levels of internalizing and externalizing problems, and PLEs (mean ratios, 0.84-0.86, all P < 0.02), adjusting for baseline scores. The associations persisted after additionally adjusting for the adolescents' polygenic risk for CUD among White participants. Family conflict and sleep problems mediated the associations of cessation with internalizing (proportion mediated, 6.8% and 25.8%, respectively) and externalizing symptoms (14.3% and 24.8%, respectively). Adolescents with weaker connections between cingulo-parietal and dorsal attention networks showed stronger associations between cessation and PLEs.

Conclusions: Household cannabis cessation was linked to a lower level of adolescent mental health problems at follow-up. These findings suggest that interventions aimed at reducing or eliminating household cannabis exposure may be beneficial for youth well-being.

Background: Existing aging clocks, designed to quantify biological aging, primarily capture systemic changes and may overlook alterations crucial for cardiometabolic diseases (CMDs).

Methods: In this study, we developed the CardioMetAge model, an aging clock tailored to predict CMD-related outcomes. Trained in the NHANES-III, the model was applied to the continuous NHANES and UK Biobank. Its associations with cardiometabolic mortality, disease incidence, and transitions between disease states were examined, and its performance in predicting 10-year CMD incidence was also evaluated. We further investigated associations of proteomic pathways, lifestyle factors, and socioeconomic status with CardioMetAge, as well as the impact of caloric restriction intervention on its change.

Results: The final CardioMetAge was constructed as a linear combination of chronological age and 12 common clinical biomarkers. Its age deviation (CardioMetAgeDev) showed stronger associations with CMD mortality (HR per SD [95% CI]: 1.87 [1.83, 1.91]), CMD incidence (1.35 [1.33, 1.37]), and disease progression, including transitions from no CMD to first CMD (1.34 [1.32, 1.35]) and from first CMD to cardiometabolic multimorbidity (1.25 [1.21, 1.30]), compared with deviations of PhenoAge and other traditional biological age models. CardioMetAge also consistently outperformed these models in predicting 10-year CMD incidence. Our findings also highlighted the biological determinants of cardiometabolic aging, with proteomic analyses linking CardioMetAgeDev to inflammatory activation and metabolic disorders. Analysis of modifiable factors revealed that lifestyle and socioeconomic status were associated with CMD risks, partly via CardioMetAgeDev (mediation proportions: 34.5% and 10.7%, respectively). Additionally, two-year caloric restriction slowed the progression of CardioMetAge by 1.23 years (95% CI: [0.61, 1.84]) relative to the ad libitum control.

Conclusions: CardioMetAge outperformed existing aging clocks in ease of use and in predicting CMD-related outcomes. It provides valuable insights into the mechanisms of cardiometabolic aging and holds potential for clinical monitoring and evaluating the effectiveness of interventions.

Background: Opioid use for chronic non-cancer pain remains common in the UK, despite limited evidence of long-term effectiveness. Delirium, a serious acute confusional state associated with increased mortality, is a known adverse effect of opioid use. Pharmacological differences between opioids may influence delirium risk, but comparative evidence is scarce. This study evaluated the association of opioid type and dosage with the risk of in-hospital delirium in non-cancer patients.

Methods: We conducted a retrospective cohort study using electronic health records (EHRs) from a tertiary care hospital in northwest England (September 26, 2014-December 31, 2020). Adult (≥ 18 years) without cancer who were administered with opioids during admission were included. Delirium was identified using the 4 'A's Test or through a combination of ICD-10 codes and new-onset confusion scores (= 3) on the National Early Warning Score. Daily opioid doses were converted to daily morphine milligram equivalents (MME/day) to assess the effect of dose across different opioid types. Incidence rates were calculated by opioid type and opioid dosage. Cox regression models, adjusted for confounders, were used to evaluate delirium risk.

Results: Among 50,586 opioid-exposed patients (mean [SD] age, 55 [20] years; 53% female), 867 patients (1.7%) experienced delirium during their first hospital admission (mean [SD] age, 75.1 [16.7] years). Compared to codeine, oxycodone (hazard ratio [HR] 3.52, 95% CI 2.77-4.46), fentanyl (HR 2.45, 95% CI 1.71-3.51), buprenorphine (HR 2.43, 95% CI 1.54-3.82), combination opioids (HR 2.22, 95% CI 1.63-3.02), and morphine (HR 2.15, 95% CI 1.65-2.79) were associated with significantly higher delirium risk. No clear dose-response association was observed: doses of 50-119 MME/day were not associated with a significant increase in risk compared to < 50 MME/day (HR 0.96, 95% CI 0.66-1.39).

Conclusions: Using in-hospital medication administration records to capture opioid exposure, we found that oxycodone, fentanyl, buprenorphine, morphine, and combination opioids were associated with increased delirium risk compared with codeine. Oxycodone was associated with a higher risk of delirium compared with both codeine and morphine. These findings support personalised opioid prescribing in non-cancer pain and can inform shared clinical decision-making to prevent delirium in patients prescribed opioids.

Background: Warming temperatures add to the global health burden, with disproportionate effects on pregnant women and newborns. Low birth weight is a major neonatal health issue in Pakistan, leading to neonatal mortality and impaired long-term health. We assessed the impact of extreme temperatures on low birth weight, identified high-risk subgroups, estimated the heat-attributable burden, projected future risks, and constructed a district-level heat vulnerability index.

Methods: We conducted a space-time series study using nationally representative surveys from 2008 to 2017 across Pakistan's provinces. We modelled temperature-low-birth-weight associations with distributed-lag non-linear models in a generalised mixed-effects framework, with model averaging to address specification uncertainty. Subgroup analyses considered maternal education, household wealth, urban/rural residence, and air quality. We estimated heat-related population attributable fraction using observed temperature and projections under SSP2-4.5 and SSP5-8.5. Province-level risk estimates combined with district-level indicators, such as mean temperature, multidimensional poverty, and under-5 mortality, were used to develop the heat vulnerability index.

Results: The study included 85,017 participants, with 15,920 (18.72%) infants identified as having low birth weight. Heat-related risks for low birth weight varied across provinces, with relative risks ranging from 1.47 (1.07-2.03, 95% confidence interval) to 1.91 (1.24-2.93) at the 99th percentile of temperature. The heat-related population attributable fraction ranged from 9.39% to 13.15%, translating to 1.24 million heat-related low-birth-weight cases over the study period. Projections indicate that heat-related population attributable fractions will increase by 8.43-10.20% by the 2060s. Subgroup analysis showed higher risk among women exposed to hazardous air pollution, those with less education, and urban residents. Women in southern Punjab, northern Baluchistan, and Sindh faced the highest risks.

Conclusions: Our findings identify Pakistan's districts most vulnerable to heat-related low birth weight and highlight contributing factors. These insights can inform targeted interventions to mitigate risks. The study advances the understanding of the impacts of rising temperatures, particularly in resource-limited and high-risk settings.

Background: It remains unclear whether reengaging in lifestyle weight loss interventions is effective for the long-term.

Methods: We conducted the CENTRAL (trial 1, T1) lifestyle weight-loss trial in 2012-2014, and the DIRECT-PLUS (trial 2, T2) weight-loss trial in 2017-2018. All participants were invited for follow-up in 2022-2024 to assess weight, metabolic biomarkers, and fat depots via magnetic-resonance-imaging (MRI) five years after the second trial.

Results: The analysis included 572 trial observations contributed by 480 participants; of these, 388 participated in one of the two trials and 92 participated in both (T1 + T2 rejoiners). At follow-up, 384/480 (80%) were re-evaluated, including 76/92 (83%) rejoiners. In T1, participants who participated once and those who later rejoined T2 exhibited similar responses to their first intervention, including comparable weight-loss (-3.3% vs. -3.4%; FDR = 0.93). However, T1 + T2 rejoiners began their second intervention with a similar baseline BMI to their first (31.8 kg/m² vs. 31.3 kg/m²; FDR = 0.12). Nevertheless, they presented a more favourable abdominal fat and metabolic profiles at T2 baseline than at their initial T1 baseline (visceral adipose tissue (VAT): 135.5 cm² vs. 160.0 cm²; homeostatic model assessment of insulin resistance (HOMA-IR): 3.8 vs. 4.5; high density lipoprotein cholesterol (HDL-C)/Triglycerides: 3.6 vs. 4.2; all FDR < 0.05). In response to T2, rejoiners exhibited attenuated improvements compared to those achieved during their previous T1 intervention (weight: -1.5% vs. -3.5%; VAT: -7.2% vs. -33.3%; deep subcutaneous adipose tissue (SAT): -4.0% vs. -31.9%; superficial SAT: -3.3% vs. -25.4%; all FDR < 0.05), and compared to first-time T2 participants (weight: -3.5%; FDR < 0.05, VAT: -11.6%; FDR = 0.20, deep SAT: -9.9%; FDR < 0.05, superficial SAT: -9.3%; FDR = 0.05). Yet, 5 years after completing T2, T1 + T2 rejoiners exhibited significantly less weight regain compared with first-time T2 participants (+ 0.2% vs. + 2.9%; FDR < 0.05), deep-SAT regain (+ 2.4% vs. + 13.3%; FDR < 0.05), and superficial-SAT regain (+ 12.8% vs. + 24.3%; FDR < 0.05), though similar VAT regain. Overall, although T1 + T2 rejoiners had higher baseline obesity parameters than first-time participants, they presented comparable values by the 5- and 10-year follow-up.

Conclusions: Despite an attenuated weight-loss response, repeated engagement in a structured lifestyle intervention yields meaningful long-term impacts with sustainable metabolic benefits.

Trial registration: CENTRAL (Clinical-trials-identifier:NCT01530724); DIRECT-PLUS (Clinical-trials-identifier:NCT03020186).

Background: Cytotoxic T-cell-mediated tumor lysis is a key mechanism of oncolytic virotherapy. While oncolytic viruses expressing bispecific T-cell engagers (BiTE) enhance tumor targeting, they lack costimulatory signals, leading to T-cell exhaustion. We developed an oncolytic adenovirus expressing a trispecific T-cell engager (TriTE) to improve antitumor responses in colorectal carcinoma models.

Methods: An oncolytic adenovirus (Ad5-TriTE) was engineered to express a TriTE molecule targeting EpCAM (tumor antigen), CD3ε (T-cell activation), and 4-1BB (co-stimulation). For comparison, a BiTE-expressing virus (Ad5-BiTE) lacking 4-1BB was used. BiTE (αCD3ε-αEpCAM) facilitates T-cell redirection, whereas TriTE (αCD3ε-α4-1BBL-αEpCAM) adds co-stimulation for enhanced T-cell activation. Antitumor efficacy was evaluated in syngeneic and humanized colorectal carcinoma mouse models.

Results: Ad5-TriTE demonstrated efficient tumor infection and TriTE secretion, leading to superior tumor control compared to Ad5-BiTE. Enhanced CD8 + T-cell infiltration and activation correlated with improved antitumor effects in both subcutaneous and peritoneal metastasis models. The humanized version, Ad5-hTriTE, exhibited potent activity in a humanized colon cancer model.

Conclusions: Oncolytic adenovirus armed with TriTE enhances antitumor immunity by integrating costimulatory signaling. Incorporating costimulatory molecules into oncolytic virotherapy may offer more effective cancer immunotherapy strategies.

Background: Cholangiocarcinoma (CCA) remains a highly lethal malignancy with a dismal prognosis, primarily driven by therapeutic resistance. A dominant resistance mechanism involves overexpression of anti-apoptotic BCL-2 proteins (BCL-XL, BCL-2, MCL-1). While direct inhibition of these proteins shows efficacy, its clinical utility is frequently limited by dose-dependent hematotoxicity-as exemplified by ABT263, a BCL-XL/BCL-2 dual inhibitor that induces severe thrombocytopenia.

Methods: We performed integrated analyses of BCL-2 family mRNA/protein expression in clinical CCA specimens and preclinical cell lines. Leveraging proteolysis-targeting chimera (PROTAC) technology, we investigated the therapeutic application of BCL-XL-specific degraders, both as monotherapy and in combination with gemcitabine, to selectively target CCA cells while minimizing hematologic toxicity.

Results: Integrated clinical-experimental data identified BCL-XL as a principal determinant of therapeutic sensitivity in CCA. In vitro, the cereblon (CRBN)-based PROTAC XZ739 demonstrated superior efficacy to its von Hippel-Lindau tumor suppressor (VHL)-based counterpart DT2216, reducing CCA cell viability via apoptosis induction. In vivo, XZ739 synergized with gemcitabine to suppress tumor growth in a CCA xenograft model, achieving robust efficacy without significant thrombocytopenia-a critical advance over conventional BCL-XL inhibitors.

Conclusions: These findings establish XZ739 as a promising therapeutic candidate for BCL-XL-dependent CCA, highlighting its translational potential for rational combination with chemotherapy to overcome resistance while mitigating hematologic toxicity.

Background: Light exposure over 24 h is a modifiable environmental influence on human physiology and behavior with significant implications for health and well-being, yet the field lacks coordinated research infrastructure, standardized methodologies, and translational pathways.

Methods: To address this, we convened a multi-disciplinary consensus workshop and expert consultation process with 13 experts from academia, public health, radiation protection, and occupational health institutions. The aim was to identify key research gaps and to define priority areas to guide future work.

Results: Through an in-person and hybrid meeting, followed by iterative refinement and feedback, we identified nine critical gaps: (1) lack of standardized measurement tools, (2) inadequate exposure estimation infrastructure, (3) inconsistent descriptors and metrics, (4) absence of outcome standards, (5) limited dose-response evidence beyond the laboratory, (6) insufficient data on intervention effectiveness, (7) poor characterization of globally representative and vulnerable populations, (8) fragmented data harmonization, and (9) limited integration into public health frameworks. To address these gaps, we propose 11 research priority areas spanning measurement, methodology, data infrastructure, ethics, and implementation, as well as four capacity-building priority areas.

Conclusions: This agenda provides a strategic foundation for building an integrated and evidence-based approach to studying and understanding light exposure as a determinant of health.

Background: As the number and complexity of patients living with serious illness continue to rise, delivering care that is both effective and responsive to individual life contexts has become increasingly important. Despite its potential benefits, the implementation of contextualized care in the management of serious illness remains limited and poorly understood. To address this gap, this study aimed to identify barriers and facilitators influencing the delivery of contextualized care for patients with serious illness, as perceived by healthcare professionals (HCPs), and to generate recommendations for improving its implementation.

Methods: Three focus groups were conducted with 20 HCPs from multiple disciplines and hospital settings in the Netherlands, all involved in the care of patients with serious illness. Discussions were guided and analysed using a directed content analysis informed by the COM-B model (Capability, Opportunity, Motivation-Behaviour) combined with the Theoretical Domains Framework. Factors were mapped to intervention functions from the Behaviour Change Wheel (BCW) to provide recommendations.

Results: Nine factors influencing contextualized care were identified across COM-B components. Capability-related factors included skills and knowledge to engage with the relevant patient context and the ability to distinguish between general and clinically relevant context. Opportunity-related factors included environmental conditions, fragmented information systems, systemic incentives misaligned with contextual care, a lack of shared team norms, collaboration challenges, and the perceived emotional complexity of contextual conversations in the palliative phase. Motivation-related factors included strong intrinsic commitment to person-centred care and awareness of the consequences of overlooking context for patients, HCPs, and the overall system. Most barriers were concentrated in the Opportunity component, with environmental and team-level constraints often outweighing individual motivation and basic skills.

Conclusions: Delivering contextualized care for patients with serious illness is not primarily limited by individual willingness or basic capability but by environmental and systemic feasibility. Sustainable implementation requires multilevel strategies targeting team culture, interprofessional collaboration, and a supportive infrastructure. Moving from individual intent to shared norms may improve both patient outcomes and resource efficiency. Key steps include continuous education, embedding contextual care in team culture, adapting workflows and documentation, and integrating contextualization into quality measures and incentives.